Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2024-55228 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Dolibarr Dolibarr Erp\/Crm. Its CVSS base score is 9.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 44th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-55228 is a cross-site scripting (XSS) vulnerability (CWE-79) in the Product module of Dolibarr version 21.0.0-beta. It allows attackers to execute arbitrary web scripts or HTML via a crafted payload injected into the Title parameter. The vulnerability has a CVSS v3.1 base score of 9.0 (AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H), indicating critical severity due to its network accessibility, low complexity, and potential for high impacts across confidentiality, integrity, and availability.
An authenticated attacker with low privileges (PR:L) can exploit this vulnerability over the network with low complexity, though it requires user interaction (UI:R). By injecting a malicious payload into the Title parameter in the Product module, the attacker can execute arbitrary scripts in the context of other users' browsers, potentially leading to session hijacking, data theft, or further compromise given the cross-scope impact (S:C) and high effect on CIA triad components.
Mitigation involves applying patches from Dolibarr repository commits such as 56710ce9b79a97df093f586c90bdaf6cce6a5808, 9aa24d9d9aeab36358c725dae3fe20c9631082e7, and c0250e4c9106b5c889e512a4771f0205d4f99b99. A proof-of-concept is available in the referenced GitHub Gist. Additional guidance is provided in Dolibarr's security policy at https://github.com/Dolibarr/dolibarr/security/policy. Security practitioners should ensure systems are updated beyond v21.0.0-beta.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-0206
Vulnerability Data
A cross-site scripting (XSS) vulnerability in the Product module of Dolibarr v21.0.0-beta allows attackers to execute arbitrary web scripts or HTMl via a crafted payload injected into the Title parameter.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.